Research on bulk-cargo-port berth assignment based on priority of resource allocation

Chunfang Guo, Zhongliang Guan, Yan Song

Abstract


Purpose: The purpose of this paper is to propose a Priority of Resource Allocation model about how to utilize the resources of the port efficiently, through the improvement of traditional ant colony algorithm, the ship-berth matching relation constraint matrix formed by ontology reasoning.

Design/methodology/approach: Through questionnaires?Explore factor analysis (EFA) and principal component analysis, the authors extract the importance of the goods, the importance of customers, and type of trade as the main factors of the ship operating priority. Then the authors combine berth assignment problem with the improved ant colony algorithm, and use the model to improve ship scheduling quality. Finally, the authors verify the model with physical data in a bulk-cargo-port in China.

Findings: Test by the real data of bulk cargo port, it show that ships’ resource using priority and the length of waiting time are consistent; it indicates that the priority of resource allocation play a prominent role in improving ship scheduling quality.

Research limitations: The questionnaires is limited in only one port group, more  related Influence factors should be considered to extend the conclusion.

Practical implications: The Priority of Resource Allocation model in this paper can be used to improve the efficiency of the dynamic berth assignment.

Originality: This paper makes the time of ship in port minimized as the optimization of key indicators and establishes a dynamic berth assignment model based on improved ant colony algorithm and the ontology reasoning model.


Keywords


ship-scheduling system, priority of resource allocation, ontology reasoning, dynamic berth assignment

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DOI: http://dx.doi.org/10.3926/jiem.673


Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Journal of Industrial Engineering and Management, 2008-2019

Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008

Publisher: OmniaScience